This document describes a study comparing PI control and fuzzy logic control for controlling the speed of a brushless DC motor. It first provides background on brushless DC motors and their mathematical modeling. It then discusses using a PI controller and fuzzy logic controller for speed control. The key finding is that a fuzzy-PI controller, which uses fuzzy logic to tune the gains of a PI controller, provides better dynamic response than a simple PI controller or fuzzy logic controller alone, with less overshoot and faster settling time. Hardware results confirmed the simulation results that the fuzzy-PI controller improved motor speed response characteristics.

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Volume: 06 Issue: 03 | Mar 2019 www.irjet.net p-ISSN: 2395-0072
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DESIGN AND IMPLEMENTATION OF ACCELERATION AND SPEED
CONTROL UNIT FOR ECO VEHICLE (SOLAR)
V. Manikandan1, D. Shenbagadevi2, T. Nirmala3, R. Karthik4
1,2,3UG Student, Valliammai Engineering College, Chennai, Tamil Nadu, India
4Associate Professor, Valliammai Engineering College, Chennai, Tamil Nadu, India
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Abstract - This paper explores the different ways to
control speed by using simple PI control and Fuzzy
logic control of permanent magnet brushless DC motor
(BLDC). There are many effective ways to control the
speed of a BLDC motor. That can be achieved by using
simple PI logic control or Fuzzy logic control. By using
PI logic control we can control the motor speed by
closed-loop control method. But in that way, we
cannot control the speed of the motor accurately
because of less number of logic we are using. This can
be rectified by using simple Fuzzy logic control. By
using fuzzy logic control the motor speed can be
controlled accurately with high response time. So in
this paper, we are going to study about a comparative
study of simple PI control and Fuzzy logic control.
Key Words: Permanent Magnet Brushless DC Motor
(PMBLDC); simple PI Logic control; Fuzzy logic control;
Microcontroller;
1. INTRODUCTION
The rapid requirement of electric drives with the
new technology in the various industries are
increases day by day. There is great demand for
efficient variable speed, long term stability and good
transient performance of motor drives. The dc motor
may be categorized according to the commutation
circuit. One is traditionally DC motor which is
mechanically commutated and other is Permanent
Magnet Brushless DC motor (BLDC) having an
electronically commutated with sensor or sensor-
less system. The BLDC motor has a rotating
permanent magnet and stationary armature [1]. It
has many advantages such as simple structure, high
reliability, small size, high torque and simple
structure. It is mainly applicable for high
performance drives. Generally the performance of
motor is affected by sudden change in unknown load
or speed. But as the BLDC motor drive are non-linear
in nature, they require an improved or modified
controller that can adapt a non-linear condition and
achieve the desired performance [2]. So to encounter
this problem controller is required. Because of the
simplicity in tuning, the PI controller are until now
are mostly useful controller in industries. The PI
controller is carried out from the input and feedback
signal [3]. But this controller is fails to operate in
dynamic conditions. While comparing with the Fuzzy
logic controller, PI controller takes large number of
peak overshoot that affects the system performance.
The hybrid Fuzzy tuned with conventional PI
controller improves the dynamic as well as steady
state behavior and also it improves the system
performance. The proposed system are analyzed
with the help of MATLAB and compared with PI
controller and simple FLC.
2. MATHEMATICAL MODELLING OF BLDC
MOTOR
The BLDC motor is working as same as the
traditional DC motor, but it is construction wise
different from it. It is a self-rotating synchronous
machine whose stator is similar to that of an
induction motor and the rotor has permanent
magnet which is rotating part. BLDC has no brushes
and commuters, instead of this it is replaced by
electronically commutated system. Current polarity
can be reversed by switches like MOSFET or IGBT for
the three phase inverter circuit in synchronization
with rotor position. This rotor position can be sensed
using Hall Effect sensor encapsulated in the stator.
The drive can be controlled in sensor or sensor-less
mode. The sensor-less mode can be reduced its cost
and sizes but its performance is poor. So in this paper
we use Hall Effect sensor. The schematic
representation of equivalent BLDC motor dive is as
shown in fig 1.

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Fig. 1. Equivalent circuit of BLDC motor drive [5]
Where Vab, Vbc, Vca are the phase voltages,
Vab = R (ia - ib) + (L – M) d/dt (ia - ib) + eab (1)
Vbc = R (ib – ic) + (L – M) d/dt (ib – ic) + ebc (2)
Vca = R (ic – ia) + (L – M) d/dt (ic – ia) + eac (3)
and ia, ib, ic are the stator phase currents, R is the
stator resistance, L is the self- inductance and M is
the mutual inductance.
The condition for the stator current to be balance is,
ia + ib + ic = 0 (4)
The developed torque, load torque and output power
is related as follows:
Te – TL = j G m /dt + m ȕ (5)
Where km is the rotor speed, Ke is the back emf
constant.
3. BLDC MOTOR WORKING
Permanent Magnet Synchronous Motor (PMSM) has
two types of excitation model; sinusoidal and
another one is trapezoidal. PMSM having a
trapezoidal excitation is called as the Permanent
Magnet Brushless DC Motor (PMBDCM). In a BLDC
motor, stator contains three phase windings and the
rotor segment is made up of permanent magnet and
consist of 2 to 8 pole pairs with alternate pairs of
North (N) and South (S) poles. In a conventional DC
motor, the commutation of a BLDC motor is carried
out using electronic switches. To operate BLDC
motor, sequential excitation must be provided. For
this, details of the rotor position are required so that
the coils will be excited. Hall based sensors placed in
the stator. Generally BLDC motor consists of Hall
sensors placed on the stator providing positioning of
rotor and it is also connected at the off-driving end of
the motor. As the magnetic poles of the rotor crosses
the Hall sensors, they give out a high or low signal,
corresponding to the North or South Pole close to the
sensors, these two fields are orthogonal to each other
and reduces gradually as the fields stay together.
Unidirectional torque can be produced by the flux
produced by the windings should catch up with the
rotor. BLDC motors mostly finds application with the
operation at medium and very high speeds. As these
kind of motors shows less inertia with high peak
torque characteristics, the motor matches for quick
acceleration and deceleration of drives. BLDC With
the help of speed feedback (speed sensor) or by a
sensor less mode (without a speed feedback) motors
can be controlled. During the normal speed control of
such type of drives, an encoder measures the speed
and compares it with a reference speed in-turn
controlling the PWM switching process.
Figure.2 BLDC Motor[6]
PWM technique is a most commonly used technique
for the power control to an electrical device, made
practical by modern electronic power switches. The
average value of voltage (and current) given to the
load is controlled by turning on and off the switch
between supply and load. Longer the switch is in ON
condition compared to that of the OFF periods, the
higher will be the power supplied to the load. The
PWM switching frequency should be as faster as it
can, than what would affect the load.

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4. Fuzzy – PI controller
The simple FLC is though it better than a
conventional PI controller but it is not used in
industries everywhere because it is auto tuning
controller. Also it has disadvantage as it takes more
memory and time consuming controller to simulate
it. So this drawback obtained from the simple FLC are
overcomed by Fuzzy – PI controller. The proposed
controller in this paper is a Mamdani fuzzy controller
which works on the principle of two input and single
output.
Fig. 3. Structure of Fuzzy tuned PI controller
It is used to calculate the speed controller is
more quickly and hence it does not take a more time
to computation and so that the memory. The design
algorithm of proposed system is just to adjust the KP
and KI parameter used on the speed error e and rate
of change speed error to control the speed in static
and dynamic condition.
Fig. 4. Simulink model of BLDC motor using Fuzzy–PI
controller
Fig. 5. Subsystem of Fig. 4
The graphical representation of above simulink
model is shown in following diagram. The Speed Vs
time for Fuzzy – PI controller is shown in Fig 4. This
shows that it has rising time is 0.002 sec and it settle
down at 0.015 sec by maintaining the overshoot 6.6
% which is less as compared to simple FLC and
conventional PI controller.
Fig. 6. Speed Vs time for Fuzzy – PI controller
Fig. 7. Stator current Vs Time for Fuzzy – PI
controller.
Fig. 8. Electromagnetic torque Vs time for Fuzzy – PI
controller.

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Fig. 9. Gate signal
5. CHARACTERISTICS OF SPEED RESPONSE
TABLE I. CHARACTERISTICS OF SPEED RESPONSE
6. HARDWARE SETUP
The hardware setup of closed loop speed control
of BLDC motor drive is shown in Figures. The
waveforms are obtained when the motor was
programmed to run at rated speed.
Fig 10. Hardware setup
7. CONCLUSION
The main problems occurred in controlling the
BLDC motor is on their characteristic and hence it is
very important to solve the problem, as use of BLDC
motor is quite large. The proposed system is
improving the operating characteristic such as its
percentage overshoot rise time and settling time etc.
It is obtained during the analysis near about 6.6%
which is good with the help of only 21 linguistics
rules so as to reduce memory.
8. REFERENCES
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5. International Research Journal of Engineering and Technology (IRJET) e-ISSN: 2395-0056
Volume: 06 Issue: 03 | Mar 2019 www.irjet.net p-ISSN: 2395-0072
© 2019, IRJET | Impact Factor value: 7.211 | ISO 9001:2008 Certified Journal | Page 1535
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